
"""simple docstring"""

from .integrations import (
    is_optuna_available,
    is_ray_available,
    is_sigopt_available,
    is_wandb_available,
    run_hp_search_optuna,
    run_hp_search_ray,
    run_hp_search_sigopt,
    run_hp_search_wandb,
)
from .trainer_utils import (
    HPSearchBackend,
    default_hp_space_optuna,
    default_hp_space_ray,
    default_hp_space_sigopt,
    default_hp_space_wandb,
)
from .utils import logging


SCREAMING_SNAKE_CASE_            =    logging.get_logger(__name__)
class   _UpperCAmelCase				:
      __SCREAMING_SNAKE_CASE :				int				   =						4_2
      __SCREAMING_SNAKE_CASE :				Tuple				   =						None




      @staticmethod
      def      a_   (				)    ->       List[str]:
          raise NotImplementedError




      def      a_   (				self ,							lowercase_ ,							lowercase_ ,							lowercase_ ,							**lowercase_				)    ->       List[str]:
          raise NotImplementedError




      def      a_   (				self ,							lowercase_				)    ->       Optional[int]:
          raise NotImplementedError




      def      a_   (				self				)    ->       str:
          if not self.is_available():
              raise RuntimeError(
                  F"You picked the {self.name} backend, but it is not installed. Run {self.pip_install()}."				)




      @classmethod
      def      a_   (				cls				)    ->       Any:
          return F"`pip install {cls.pip_package or cls.name}`"

class   _UpperCAmelCase				(		_lowerCAmelCase				):
      __SCREAMING_SNAKE_CASE :				Union[str, Any]				   =						"optuna"




      @staticmethod
      def      a_   (				)    ->       List[str]:
          return is_optuna_available()




      def      a_   (				self ,							lowercase_ ,							lowercase_ ,							lowercase_ ,							**lowercase_				)    ->       List[str]:
          return run_hp_search_optuna(SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_				)




      def      a_   (				self ,							lowercase_				)    ->       Any:
          return default_hp_space_optuna(SCREAMING_SNAKE_CASE_				)

class   _UpperCAmelCase				(		_lowerCAmelCase				):
      __SCREAMING_SNAKE_CASE :				Union[str, Any]				   =						"ray"
      __SCREAMING_SNAKE_CASE :				str				   =						"\'ray[tune]\'"




      @staticmethod
      def      a_   (				)    ->       Optional[Any]:
          return is_ray_available()




      def      a_   (				self ,							lowercase_ ,							lowercase_ ,							lowercase_ ,							**lowercase_				)    ->       Optional[Any]:
          return run_hp_search_ray(SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_				)




      def      a_   (				self ,							lowercase_				)    ->       List[Any]:
          return default_hp_space_ray(SCREAMING_SNAKE_CASE_				)

class   _UpperCAmelCase				(		_lowerCAmelCase				):
      __SCREAMING_SNAKE_CASE :				int				   =						"sigopt"




      @staticmethod
      def      a_   (				)    ->       Any:
          return is_sigopt_available()




      def      a_   (				self ,							lowercase_ ,							lowercase_ ,							lowercase_ ,							**lowercase_				)    ->       str:
          return run_hp_search_sigopt(SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_				)




      def      a_   (				self ,							lowercase_				)    ->       List[str]:
          return default_hp_space_sigopt(SCREAMING_SNAKE_CASE_				)

class   _UpperCAmelCase				(		_lowerCAmelCase				):
      __SCREAMING_SNAKE_CASE :				Union[str, Any]				   =						"wandb"




      @staticmethod
      def      a_   (				)    ->       List[Any]:
          return is_wandb_available()




      def      a_   (				self ,							lowercase_ ,							lowercase_ ,							lowercase_ ,							**lowercase_				)    ->       int:
          return run_hp_search_wandb(SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_				)




      def      a_   (				self ,							lowercase_				)    ->       Tuple:
          return default_hp_space_wandb(SCREAMING_SNAKE_CASE_				)

SCREAMING_SNAKE_CASE_            =    {
    HPSearchBackend(backend.name): backend for backend in [OptunaBackend, RayTuneBackend, SigOptBackend, WandbBackend]
}




def      lowercase__    (       )			->   Optional[Any]:






    """simple docstring"""




    UpperCAmelCase          =       [backend for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values() if backend.is_available()]
    if len(lowerCAmelCase__			) > 0:
        UpperCAmelCase          =       available_backends[0].name
        if len(lowerCAmelCase__			) > 1:
            logger.info(
                F"{len(lowerCAmelCase__			)} hyperparameter search backends available. Using {name} as the default."			)
        return name
    raise RuntimeError(
        'No hyperparameter search backend available.\n'
        + '\n'.join(
            F" - To install {backend.name} run {backend.pip_install()}"
            for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values()			)			)








from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


a      :  Dict			     =			{
    'configuration_lxmert': ['LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LxmertConfig'],
    'tokenization_lxmert': ['LxmertTokenizer'],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a      :  Any			     =			['LxmertTokenizerFast']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a      :  str			     =			[
	    'LxmertEncoder',
	    'LxmertForPreTraining',
	    'LxmertForQuestionAnswering',
	    'LxmertModel',
	    'LxmertPreTrainedModel',
	    'LxmertVisualFeatureEncoder',
	    'LxmertXLayer',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a      :  str			     =			[
	    'TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'TFLxmertForPreTraining',
	    'TFLxmertMainLayer',
	    'TFLxmertModel',
	    'TFLxmertPreTrainedModel',
	    'TFLxmertVisualFeatureEncoder',
	]


if TYPE_CHECKING:
	from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
	from .tokenization_lxmert import LxmertTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_lxmert_fast import LxmertTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_lxmert import (
		    LxmertEncoder,
		    LxmertForPreTraining,
		    LxmertForQuestionAnswering,
		    LxmertModel,
		    LxmertPreTrainedModel,
		    LxmertVisualFeatureEncoder,
		    LxmertXLayer,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_lxmert import (
		    TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFLxmertForPreTraining,
		    TFLxmertMainLayer,
		    TFLxmertModel,
		    TFLxmertPreTrainedModel,
		    TFLxmertVisualFeatureEncoder,
		)

else:
	import sys

	a      :  str			     =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






